System and method for real-time fault detection, classification, and correction in a semiconductor manufacturing environment

ABSTRACT

A system and method for detecting a fault and identifying a remedy for the fault in real-time in a semiconductor product manufacturing facility are provided. In one example, the method includes importing data from a manufacturing device and data representing a plurality of different manufacturing devices into an analysis tool. The imported data is analyzed using the analysis tool to determine if a fault exists in the manufacturing device&#39;s operation and, if a fault exists, the fault is classified and a remedy for the fault is identified based at least partly on the classification. Configuration data used to control the manufacturing device may be updated, and the update may apply the remedy to the configuration information. The manufacturing device&#39;s operation may then be modified using the updated configuration data.

CROSS-REFERENCE

This application is related to U.S. patent application Ser. No.10/831,064, filed on Apr. 23, 2005, and entitled “A SYSTEM AND METHODFOR IMPROVING EQUIPMENT COMMUNICATION IN A SEMICONDUCTOR MANUFACTURINGENVIRONMENT.”

TECHNICAL FIELD

The present disclosure relates generally to semiconductor manufacturingand, more specifically, to a computer-based system for fault detectionand classification in a semiconductor 3manufacturing facility.

BACKGROUND

In a semiconductor manufacturing business, manufacturing equipment maybe used to perform operations such as processing semiconductor wafers,monitoring such processing, transferring wafers between pieces ofequipment, and performing similar functions. Due to the complex natureof semiconductor processing, multiple variables may be monitored at anygiven time. For example, processing equipment may perform processing ina chamber that is controlled by such parameters as pressure,temperature, and duration of processing time. Tracking these parametersmay result in a relatively large amount of data that makes identifyingfaults in the processing equipment's operation difficult and maylengthen the amount of time needed to respond to such a fault.

Accordingly, what is needed in the art is an improved system and methodfor identifying and addressing faults in a semiconductor manufacturingenvironment.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a schematic view of one embodiment of a faultdetection and classification system according to aspects of the presentdisclosure.

FIG. 2 is a flowchart of an exemplary method for retrieving andanalyzing data that may be executed within the system of FIG. 1.

FIG. 3 illustrates an exemplary data flow corresponding to the method ofFIG. 2.

FIG. 4 is a flowchart of an exemplary method for fault identificationand classification that may be executed within the system of FIG. 1.

FIG. 5 illustrates an exemplary data flow corresponding to the method ofFIG. 4.

FIG. 6 illustrates an exemplary data flow for restoring archived datawithin the system of FIG. 1.

FIG. 7 illustrates an exemplary virtual fabrication system within whichthe system of FIG. 1 may be implemented.

DETAILED DESCRIPTION

The present disclosure relates generally to semiconductor manufacturingand, more specifically, to a computer-based system for fault detectionand classification in a semiconductor manufacturing facility. It is tobe understood that the following disclosure provides many differentembodiments, or examples, for implementing different features of thedisclosure. Specific examples of components and arrangements aredescribed below to simplify the present disclosure. These are, ofcourse, merely examples and are not intended to be limiting. Inaddition, the present disclosure may repeat reference numerals and/orletters in the various examples. This repetition is for the purpose ofsimplicity and clarity and does not in itself dictate a relationshipbetween the various embodiments and/or configurations discussed.

Referring to FIG. 1, in one embodiment, a fault detection andclassification system 100 is illustrated. The system 100 supportsautomatic fault detection and classification, and may be used toautomatically implement a remedy to correct the fault. As will bedescribed later in greater detail, the system 100 may be implemented ina semiconductor manufacturing environment to handle relatively largeamounts of both real-time and delayed data. The system 100 includes ahierarchy of layers 110, 120, 130, and 140. It is understood that thelayers are illustrated for purposes of example only, and that they maybe combined and/or further divided to form many differentconfigurations. Furthermore, additional layers may be added to thesystem 100. The layers 110, 120, 130, and 140 may be connected via oneor more networks 102 for purposes of communication.

The layer 110 may include one or more tool databases 112, archive tooldatabases 114, and a database optimization process 116. The layer 110may be connected to one or more manufacturing devices 104 (e.g., processtools, sensors, etc.) via an interface 106, which is a fault detectionand classification (FDC) interface in the present example. In thepresent example, the manufacturing device 104 is a process tool, but itis understood that it may be any device or process used in asemiconductor manufacturing environment. Although the process tool 104and FDC interface 106 are not shown as part of the layer 110, it isunderstood that they may be included in the layer in some embodiments.In the present example, each process tool 104 may be associated with itsown tool database 112 from the layer 110. However, other configurationsmay provide a single tool database 112 for multiple process tools 104.If the tool database 112 is shared by multiple process tools 104, datafrom each process tool may be stored separately from data from the otherprocess tools, or the data may be combined. The tool database 112 may beconnected to a tool archive database 114, which may be used to store atleast a portion of the data from the tool database 112. As will bedescribed later in greater detail, the database optimization process 116may be used to filter data, archive data from the tool database 112 tothe archive tool database 114, and perform other tasks.

The process tool 104 may comprise an individual process reactor and/or acluster tool that is able to execute multiple processing steps for thecreation a microelectronics product. Exemplary steps may includedeposition of a refractory metal such as TiN, TaN, or WN followed by thedeposition of a Cu seed, and a bulk Cu deposition over a substrate. Theprocess tool 104 may execute processes such as chemical vapor deposition(CVD), plasma assisted chemical vapor deposition (PECVD), atomic layerdeposition (ALD), physical vapor deposition (PVD), photolithography,plasma etch, or chemical etching. The process tool 104 may also includemetrology tools for the classification of defects and features of theproduct. Such metrology tools may include scanning electron microscopes(SEM), laser surface defect scanners, optical microscopes, residual gasanalyzers, process tool particle counters, and/or a variety of othermetrology tools. The process tool 104 may further include a plurality ofsensors for monitoring pressure, gas flows, time, temperature, impuritylevels, and/or other parameters.

The FDC interface 106 may include a hardware and/or software basedinterface for the process tool 104. The FDC interface 106 may provide aninterface between the process tool 104 and a manufacturing executingsystem (MES) (not shown). The FDC interface 106 may be adapted forcommunication with other entities through wired or wireless connectionsand protocols. Wired connections may include LAN, Ethernet, and/or otherdirect wire connections, while wireless connections may includeBlueTooth®, 802.11b, 802.1 μg, and/or other wireless communicationprotocols. The FDC interface 106 may also be recognized by other devices(not shown) on the network 102 as a network entity. The FDC interface106 may connect to the process tool 104 through a semiconductorequipment communications standard (SECS) and/or generic equipment model(GEM) communication link, or by other connections as may be known by oneskilled in the art.

In some embodiments, a switching device or process may be used to aid inestablishing simultaneous connections between multiple tools/processesand the process tool 104. Such switching is described in greater detailin U.S. patent application Ser. No. 10/851,592, filed on May 20, 2004,and entitled “A SYSTEM AND METHOD FOR IMPROVING EQUIPMENT COMMUNICATIONIN A SEMICONDUCTOR MANUFACTURING ENVIRONMENT,” which is herebyincorporated by reference as if reproduced in its entirety.

The tool database 112 may include a plurality of storage devices, aswell as instructions for manipulating data received through the FDCinterface 106. The database optimization process 116 may includeinstructions for filtering, concatenating, and purging fragmentedinformation from the tool database 112. The database optimizationprocess 116 may also include instructions for maintaining predefinedfile sizes or a predefined database structure. For example, the tooldatabase 112 may utilize an online translation protocol (OLTP) that aidsin maintain relatively small file sizes. Accordingly, the databaseoptimization process 116 may maintain the file structure within the tooldatabase 112 as defined by the OLTP. The database optimization processmay provide other functionality, such as indexing data, providingstatus, dates, location, and/or other related events from the tooldatabase 112.

The tool archive database 114 may include a plurality of storage devicesto provide local and temporary storage of the information. Theinformation may include raw data obtained directly from the FDCinterface 106 and/or may include information from the tool database 112.For example, the database optimization process may extract informationfrom the tool database 112 and store it in the archive tool database 114for archival purposes.

The layer 120 includes one or more analysis databases 122 connected toone or more analysis tools 124. Instructions (not shown) for extracting,translating, and loading (collectively referred to hereinafter as an ETLprocess) may also be included in the layer 120. The analysis database122 may receive information from the tool database 112 and/or the toolarchive database 114 of the layer 110. In addition, the analysisdatabase 122 may store pre-analysis and/or post-analysis informationreceived from the analysis tool 124.

The ETL process may be used to extract specific data from the analyzedinformation after processing by the analysis tools 124-N. The ETLprocess may be used to translate the analyzed information, which mayinclude the application of rules for structuring information intoreports or other documents. For example, the ETL process may create aplurality of reports summarizing the analyzed information, and thereports may be periodically and/or continuously updated. The reportsgenerated by the ETL process may include information detailing orsummarizing the process tool 104 and its operation. The ETL process mayalso load information into a statistical process control (SPC) module inthe analysis tool 124 and/or other computing entities within otherlayers 110, 130, and 140.

The analysis tool 124 may include a plurality of analysis instructionsfor statistically summarizing the information from the layers 110, 130,and 140. The analysis tool 124 may further provide comparison analysisbetween historical information and information collected in real-timethrough the FDC interface 106 of the layer 110.

The layer 130 may include at least one configuration database 132 and atleast one cross-tool analysis database 134.

The configuration database 132 may store configuration information,process control models, and process control strategies for the processtool 104. In addition, the configuration database 132 may provideinformation used to modify the various data that affect the process tool104. For example, the information may be used to adjust a processparameter such as gas flow, chamber pressure, and/or process time. Inthis manner, optimizations and other adjustments may be made to theprocess tool 104 via the network 102.

The configuration database 132 may receive information from thecross-tool analysis database 134, the layer 140, the layer 120, and thelayer 110. The configuration database 132 may further providecorrelation analysis between the information supplied by the analysistool 124, the cross-tool analysis database 134, and other storagedevices. The correlation may provide determination of influentialprocess parameters which impact product yield and device performance.The correlation may be utilized to control correlated parameters of theprocess tool 112.

The cross-tool analysis database 134 may include information obtainedfrom multiple process tools 104. Such information may be used to analyzethe performance, yield rate, and other data of each process tool withthat of the other process tools. For example, there may be eight processtools dedicated to the same process within the semiconductor productmanufacturing facility, and the cross-tool analysis database 134 maystore similar information from each tool that may be analyzed toidentify various trends or other performance issues. In someembodiments, the analysis may include benchmarking and normalization ofthe eight process tools 104. The cross-tool analysis database 134 mayprovide instructions for implementing SPC upon the informationcomprising the cross-tool analytics database.

The layer 140 may include permanent storage (e.g., backup databases,compact disks, tapes, etc.) 142. Information may be stored to thepermanent storage 142 from one or more of the other layers 110, 120, 130periodically (e.g., upon the occurrence of an event) or at scheduledintervals.

Referring now to FIG. 2 and with additional reference to FIG. 3, anexemplary method 150 illustrates one possible flow of data through thesystem 100 of FIG. 1. In the present example, the data flow enables datafrom the process tool 104 to be retrieved, archived, and analyzedagainst other data.

In step 152, data obtained from the process tool 104 and/or the FDCinterface 106 may be stored in the tool database 112. It is understoodthat other data, such as data from a manufacturing execution system (notshown) may be included in the stored data.

In step 154, the data in the tool database 112 may be processed by thedatabase optimization process 116. The processing may includeidentifying and discarding fragmented and/or redundant data, purgingdata that is not usable (e.g., corrupt) or accessible, compressing thedata using one or more compression techniques to reduce the amount ofdata that must be stored, formatting the data to comply with apredefined format, etc.

In step 156, the data may be archived in the tool archive database 114.The data may be archived in its original form (e.g., as obtained fromthe process tool 104 and/or FDC interface 106) and/or may be archived inits processed form (after completion of step 154).

In step 158, the archived data may be moved to the file stage 144 andstored on permanent storage 142. In some embodiments, the data may bestored to the layer 140 without first storing the data on the toolarchive database 114. In the present example, the data may betransferred from the tool archive database 114 using a backup agent (notshown), which may transfer the data at predefined intervals or upon theoccurrence of a predefined event.

In step 160, processed data may be transferred from the tool database112 to the cross-tool analysis database 134. The ETL process may be usedto translate the processed data, which may include the application ofrules for structuring the data into reports or other documents. Forexample, the ETL process may create a plurality of reports summarizingthe processed data, and the reports may be periodically and/orcontinuously updated. The reports generated by the ETL process mayinclude information detailing or summarizing the process tool 104 andits operation.

In step 162, the data may be compared to other data (e.g., historicaldata and/or data from other process tools) in the cross-tool analysisdatabase 134. The comparison and/or other analysis methods may be usedto identify trends, evaluate the performance of the process tool 104,provide optimization information, and perform other analyticaloperations.

It is understood that the steps of the method 150 may be performed in adifferent order or simultaneously. For example, step 160 may occurbefore step 156, or the steps may occur simultaneously.

Referring now to FIG. 4 and with additional reference to FIG. 5, anexemplary method 170 illustrates another possible flow of data throughthe system 100 of FIG. 1. In the present example, the data flow enablesdata to be retrieved from multiple databases and analyzed, with resultsfrom the analysis being used as feedback for controlling the processtool 104. The analysis may reveal a fault in the operation of theprocess tool 104. The fault may then be classified and remedial actionmay be taken to address the fault.

In step 172, data may be imported into the tool analysis database 122from one or more of the tool database 112, the tool archive database114, and the permanent storage 142.

In step 174, the data from the tool analysis database 122 and data fromthe cross-tool analysis database may be imported into the analysis tool124. It is understood that data may be imported directly from one ormore of the process tool 104, the interface 106, the tool database 112,the tool archive database 114, and the permanent storage 142.

In step 176, the imported data may be analyzed using the analysis tool124. The analysis may identify faults (e.g., incorrect parameters suchas pressure, temperature, process time, etc.), possible optimizations,or other results. For example, data from the tool analysis database 122(storing data from the tool database 112) may be compared to data fromthe cross-tool analytic database 134 to identify operations where theperformance of the process tool 104 is lower than that of other processtools. In some embodiments, if the performance is outside of apredefined range, a fault may exist.

In step 178, a determination may be made as to whether a fault wasdetected in step 176. Additionally or alternatively, optimizations maybe identified to improve the operation of the process tool 104.

In step 180, if a fault was determined to exist in step 178, the faultmay be classified and a remedy may be identified based at least partlyon the classification. For example, the analysis may indicate that thefault stems from an incorrect pressure within a chamber of the processtool 104. The fault may then be classified as a pressure fault, and thepossible remedies for pressure faults may be examined. If the pressureis too low, a remedy may be selected that will increase the pressureuntil a predefined pressure level is attained. If the fault is outsideof certain parameters, an engineer may be notified to take correctiveaction or to further examine the problem.

In step 182, results from the analysis tool 124 may be used to updatethe configuration information in the configuration database 132. Theresults may be stored directly into the configuration database 132 ormay be formatted prior to such storage. For example, softwareinstructions may be used to select specific data from the results andsave that data into predefined configuration fields that correspond toconfiguration information needed by the process tool. The configurationupdate may include instructions needed to implement the remedyidentified in step 180 (e.g., increase the pressure).

In step 180, the updated configuration information may be transferred tothe FDC interface 106 for use in controlling the process tool 104.

Referring now to FIG. 6, an exemplary data flow within the system 100 ofFIG. 1 illustrates the retrieval of archived data from permanentstorage. This may be needed, for example, if a system failure hasdeleted or corrupted system information stored in one or more of thedatabases 112, 114, 122, 132, 134.

The archived data may first be retrieved from permanent storage 142 andsent through the file stage 144. The file stage 144 may decompress data,restore data to a predefined format, organize data in files, and performsimilar operations. It is understood that the file stage 144 may reversethese operations for files being stored to the permanent storage 142.From the file stage 144, the data may be transferred to the tool archivedatabase 114. The data may then be restored to the tool database 112.

Referring now to FIG. 7, a virtual IC fabrication system (a “virtualfab”) 200 provides an exemplary environment within which the system 100of FIG. 1 may be implemented. For example, various components of thesystem 100 may be included in or represented by the entities of thevirtual fab 200. The virtual fab 200 includes a plurality of entitiesrepresented by one or more internal entities 202, and one or moreexternal entities 204 that are connected by a communications network 206(e.g., the network 102 of FIG. 1). The network 206 may be a singlenetwork or may be a variety of different networks, such as an intranetand the Internet, and may include both wireline and wirelesscommunication channels.

Each of the entities 202, 204 may include one or more computing devicessuch as personal computers, personal digital assistants, pagers,cellular telephones, and the like. For the sake of example, the internalentity 202 is expanded to show a central processing unit (CPU) 208, amemory unit 210, an input/output (I/O) device 212, and an externalinterface 214. The external interface may be, for example, a modem, awireless transceiver, and/or one or more network interface cards (NICs).The components 208–214 are interconnected by a bus system 216. It isunderstood that the internal entity 202 may be differently configuredand that each of the listed components may actually represent severaldifferent components. For example, the CPU 208 may actually represent amulti-processor or a distributed processing system; the memory unit 224may include different levels of cache memory, main memory, hard disks,and remote storage locations; and the I/O device 212 may includemonitors, keyboards, and the like.

The internal entity 202 may be connected to the communications network206 through a wireless or wired link 218, and/or through an intermediatenetwork 220, which may be further connected to the communicationsnetwork. The intermediate network 220 may be, for example, a completenetwork or a subnet of a local area network, a company wide intranet,and/or the Internet. The internal entity 202 may be identified on one orboth of the networks 206, 220 by an address or a combination ofaddresses, such as a MAC address associated with the network interface214 and an IP address. Because the internal entity 202 may be connectedto the intermediate network 220, certain components may, at times, beshared with other internal entities. Therefore, a wide range offlexibility is anticipated in the configuration of the internal entity202. Furthermore, it is understood that, in some implementations, aserver 222 may be provided to support multiple internal entities 202. Inother implementations, a combination of one or more servers andcomputers may together represent a single entity.

In the present example, the internal entities 202 represents thoseentities that are directly responsible for producing the end product,such as a wafer or individually tested IC devices. Examples of internalentities 202 include an engineer, customer service personnel, anautomated system process, a design or fabrication facility andfab-related facilities such as raw-materials, shipping, assembly ortest. Examples of external entities 204 include a customer, a designprovider, and other facilities that are not directly associated or underthe control of the fab.

In addition, additional fabs and/or virtual fabs can be included withthe internal or external entities. Each entity may interact with otherentities and may provide services to and/or receive services from theother entities.

It is understood that the entities 202, 204 may be concentrated at asingle location or may be distributed, and that some entities may beincorporated into other entities. In addition, each entity 202, 204 maybe associated with system identification information that allows accessto information within the system to be controlled based upon authoritylevels associated with each entities identification information.

The virtual fab 200 enables interaction among the entities 202, 204 forpurposes related to IC manufacturing, as well as the provision ofservices. In the present example, IC manufacturing can include one ormore of the following steps:

-   -   receiving or modifying a customer's IC order of price, delivery,        and/or quantity;    -   receiving or modifying an IC design;    -   receiving or modifying a process flow;    -   receiving or modifying a circuit design;    -   receiving or modifying a mask change;    -   receiving or modifying testing parameters;    -   receiving or modifying assembly parameters; and    -   receiving or modifying shipping of the ICs.

One or more of the services provided by the virtual fab 200 may enablecollaboration and information access in such areas as design,engineering, and logistics. For example, in the design area, thecustomer 204 may be given access to information and tools related to thedesign of their product via the fab 202. The tools may enable thecustomer 204 to perform yield enhancement analyses, view layoutinformation, and obtain similar information. In the engineering area,the engineer 202 may collaborate with other engineers 202 usingfabrication information regarding pilot yield runs, risk analysis,quality, and reliability. The logistics area may provide the customer204 with fabrication status, testing results, order handling, andshipping dates. It is understood that these areas are exemplary, andthat more or less information may be made available via the virtual fab200 as desired.

Another service provided by the virtual fab 200 may integrate systemsbetween facilities, such as between a facility 204 and the fab facility202. Such integration enables facilities to coordinate their activities.For example, integrating the design facility 204 and the fab facility202 may enable design information to be incorporated more efficientlyinto the fabrication process, and may enable data from the fabricationprocess to be returned to the design facility 204 for evaluation andincorporation into later versions of an IC.

In the present example, multiple internal entities 202 may represent theprocess tool 104, interface 106, various databases, and other componentsof the system 100 of FIG. 1. Using the network 102 (which may form someor all of the network 206), an external entity (e.g., a customer or anoffsite engineer) may access the system 100 to restore data and performother functions. It is understood that various components of the system100 may be distributed throughout the virtual fab 200.

The present disclosure has been described relative to a preferredembodiment. Improvements or modifications that become apparent topersons of ordinary skill in the art only after reading this disclosureare deemed within the spirit and scope of the application. It isunderstood that several modifications, changes and substitutions areintended in the foregoing disclosure and in some instances some featuresof the disclosure will be employed without a corresponding use of otherfeatures. For example, various steps in the above described methods maybe combined, further divided, or eliminated entirely. Furthermore, stepsmay be performed in any order, and steps described with respect todifferent methods may be combined into a single method. In addition,data flows other than those illustrated may be used to provide identicalor similar functionally. Accordingly, it is appropriate that theappended claims be construed broadly and in a manner consistent with thescope of the disclosure.

1. A computer-executable method for detecting a fault and identifying aremedy for the fault in real-time in a semiconductor productmanufacturing facility, the system comprising: importing data from amanufacturing device into an analysis tool; importing data representinga plurality of different manufacturing devices into the analysis tool;analyzing the imported data to determine if a fault exists in themanufacturing device's operation; if a fault exists, classifying thefault and identifying a remedy for the fault based at least partly onthe classification; updating configuration data used to control themanufacturing device, wherein the updating applies the remedy to theconfiguration information; and modifying the manufacturing device'soperation using the updated configuration data.
 2. Thecomputer-executable method of claim 1 further comprising storing thedata from the manufacturing device in a tool database prior to importingthe data into the analysis tool, wherein the data is imported into theanalysis tool from the tool database.
 3. The computer-executable methodof claim 2 further comprising importing the data from the tool databaseinto an analysis database associated with the analysis tool prior toimporting the data into the analysis tool, wherein the data is importedinto the analysis tool from the analysis database.
 4. Thecomputer-executable method of claim 3 further comprising importingarchive data into the analysis database from at least one of a toolarchive database configured to archive data from the tool database, anda permanent storage.
 5. The computer-executable method of claim 2wherein the data representing a plurality of different manufacturingdevices is imported into the analysis tool from a cross-tool analysisdatabase containing comparison data from the plurality of differentmanufacturing devices.
 6. The computer-executable method of claim 5wherein updating configuration data used to control the manufacturingdevice includes storing the configuration information in a configurationdatabase accessible to an interface for the manufacturing device, andwherein modifying the manufacturing device's operation includestransferring the configuration information from the configurationdatabase to the interface.
 7. The computer-executable method of claim 1further comprising: storing data from the manufacturing device into atool database; optimizing the data in the tool database; transferringthe data from the tool database to a cross-tool analysis database; andanalyzing the data from the cross-tool analysis database by comparingthe data with data from a plurality of other manufacturing devices. 8.The computer-executable method of claim 7 wherein analyzing the datafrom the cross-tool analysis database identifies a trend in themanufacturing device's operation.
 9. The computer-executable method ofclaim 7 wherein analyzing the data from the cross-tool analysis databaseidentifies an optimization to be made in the manufacturing device'soperation.
 10. The computer-executable method of claim 7 whereinoptimizing the data includes identifying and discarding fragmented data,and compressing non-fragmented data.
 11. The computer-executable methodof claim 1 further comprising instructions for producing a reportsummarizing the analyzed data.
 12. A system for real-time faultdetection and classification in a semiconductor product manufacturingfacility, the system comprising: a tool database configured to storedata from a manufacturing device; a tool analysis database accessible tothe tool database and configured to store data for analysis by ananalysis tool; a cross-tool analysis database accessible to the toolanalysis database and configured to store data comparing a plurality ofmanufacturing devices; a configuration database accessible to theanalysis tool and configured to store data used for controlling themanufacturing device; and a plurality of software instructions forexecution within the system, the instructions including: instructionsfor importing data from the tool database into the tool analysisdatabase; instructions for importing data from the tool analysisdatabase and the cross-tool analysis database into the analysis tool;instructions for analyzing the imported data to determine if a faultexists in the manufacturing device's operation; instructions for, if afault exists, classifying the fault and identifying a remedy for thefault based at least partly on the classification; instructions forupdating the data in the configuration database using the remedy; andinstructions for modifying the manufacturing device's operation usingthe updated data from the configuration database.
 13. The system ofclaim 12 further comprising an interface accessible to the manufacturingdevice and the configuration database, wherein the instructions formodifying the manufacturing device's operation using the updated datafrom the configuration database include transferring the data from theconfiguration database to the interface.
 14. The system of claim 12further comprising a tool archive database accessible to the tooldatabase and configured to archive data from the tool database.
 15. Thesystem of claim 14 further comprising instructions for a databaseoptimization process, the instructions including: instructions forstoring data from the manufacturing device in the tool database;instructions for optimizing the data stored in the tool database; andinstructions for archiving the data in the tool database by storing thedata in the archive database.
 16. The system of claim 15 wherein theinstructions for archiving the data in the tool database includeinstructions for compressing the data.
 17. The system of claim 15wherein the instructions for optimizing the data include instructionsfor filtering fragmented data from the tool database.
 18. The system ofclaim 12 further comprising archiving files from the tool archivedatabase to a permanent storage medium.
 19. The system of claim 18further comprising instructions for restoring data from the permanentstorage medium to the tool archive database, and from the tool archivedatabase to the tool database.
 20. The system of claim 12 furthercomprising: instructions for transferring the data from the tooldatabase to the cross-tool analysis database; and instructions foranalyzing the data by comparing the data to similar data obtained from aplurality of other manufacturing devices.